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How to Learn Python Scripting in 7 Simple Steps

Python is one of the most in-demand programming languages in the world — and for good reason. Knowing how to code has never been so valuable thanks to the expanding world of tech and focus on data science. From landing high-paying jobs to improving your skillset, learning Python scripting can bring you many opportunities to succeed. However, while these opportunities are robust, many challenges come with learning Python.

How To Use Change Data Capture with Integrate.io

Change data capture (CDC) is a crucial, but also tremendously underappreciated, feature that forms the backbone of modern ETL workloads. Without knowing which data has changed since you last accessed it, you’d be forced to extract all the data from a source table or database each time that you perform data integration—which would be a tremendously inefficient process.

10 Best Practices for Building a Good API

APIs are being created faster than ever before with ever-advancing technologies such as node.js and AngularJS. With the flexibility in design and integrations for APIs, there isn't a more exciting time than now to be an API developer. However, with so many new technologies and methods of creating APIs comes the question, "What makes a good API?" While the increase in API creation has many advantages for businesses in multiple areas, there is also more room for low-quality API production.

Modern Data Stack using Integrate.io for the ELT

Integrate.io is a company that provides an ELT (Extract, Load and Transform) data stack. They can do transformations using DBT, which stands for Database Transformation toolkit. Then they use Integrate.io again to push the data into systems like Salesforce. This system will allow you to have better control over your data and provide a cost-effective solution.

Is SSIS a Good ETL Tool?

ETL (Extract, Transfer and Load) is a well-known data integration process. There is an overwhelming number of tools that you can use (one of which is SSIS) and it can be difficult to choose between them. What exactly is SSIS, and how can it help your company perform ETL better than you ever have before? This article will explain the major features of SSIS, demonstrate the pros and cons of implementing it, and advise as to when you might be better off with a different ETL tool.

What is Amazon Redshift Spectrum?

Amazon S3 (Simple Storage Service) has been around since 2006. Most use this scalable, cloud-based service for archiving and backing up data. Within 10 years of its birth, S3 stored over 2 trillion objects, each up to 5 terabytes in size. Enterprises value their data as something worth preserving. But much of this data lies inert, in “cold” data lakes, unavailable for analysis. Also called “dark data”, it can hold key insights for enterprises.

Redshift Join: How to use Redshift's Join Clause

Redshift’s JOIN clause is perhaps the second most important clause after SELECT clause, and it is used even more ubiquitously, considering how interconnected a typical application database’s tables are. Due to that connectivity between datasets, data developers require many joins to collect and process all the data points involved in most use cases. Unfortunately, as the number of tables you’re joining in grows, so does the sloth of your query.

What Are The Best ETL Tools For Vertica?

Vertica claims to offer the "most advanced unified analytical warehouse" in the world, providing actionable data insights you can't find anywhere else. The truth is, like any data warehouse, Vertica is only as good as the data you put into it. Moving data to Vertica can be a headache for organizations without a data engineering team. Data might live in various locations — transactional databases, relational databases, customer relationship management (CRM) systems, you name it.

PostgreSQL to Amazon Redshift: 4 Ways to Replicate Your Data

PostgreSQL is the preferred platform of millions of developers around the world. The open-source tool is one of the most powerful databases on the planet, with the ability to handle sophisticated analytical workloads and high levels of concurrency. That makes PostgreSQL (also called Postgres) a popular DB for scientific research and AI/ML projects. It’s also a popular production database for data-driven companies in every industry. But no database is perfect.